Stroke is one of the leading causes of death and disability in the United States. Each year more than 795,000 people in the U.S. have a stroke; over 100,000 will die and a majority of the others will suffer varying degrees of neurological injury. An NIH estimate indicated that the cost of caring for people with strokes exceeded $73 billion in U.S. healthcare dollars each year. While many advances have been made in the care of people with strokes (e.g. preventative measures and rehabilitation), once a stroke has occurred, the ability to effectively prevent or limit neurological injury remains elusive. Only a small fraction of people having an acute stroke are suitable candidates for endovascular therapy; estimates place this number between 58,000 and 120,000 per year. Critical factors which impact both the likelihood of successful revascularization and, more importantly, the chances of a good clinical outcome are: 1) the time from onset of a stroke to revascularization and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from ones where there is a large ischemic core and very little or no penumbra. It is on these two factors that we believe the application of the proposed techniques will have a quantum impact. Our overarching objective is to develop a new imaging workflow using available C-arm cone-beam CT data acquisition systems that are currently widely available in angiography suites worldwide. We believe that this new clinical paradigm will enable selected patients with an acute ischemic stroke (AIS) to be diagnosed, triaged, and treated using a single modality, thus greatly reducing delay in the time from stroke onset to treatment. The proposed imaging scheme provides imaging data that will enhance the ability to select those patients most likely to benefit from revascularization and eliminate ones for whom revascularization may be futile or potentially harmful. This new workflow is enabled by a revolutionary image reconstruction technique, namely the Synchronized Multi-Artifact Reduction with Tomographic RECONstruction (SMART-RECON) technique, invented by the PI of the project. This new reconstruction method fundamentally challenges the traditional conditions for image reconstruction written in textbooks and other recent literature: Its application enables the reconstruction of time-resolved CT images using data acquired from a series of angular segments taken over an angular span of about 60 degrees rather than the conventional standard of 180 degrees plus the fan angle. This new technique enables a quantum leap in C-arm based cone beam CT imaging, allowing one to acquire and reconstruct high temporal resolution images at ultra low radiation dose levels. These SMART- RECON processed images may then be used to generate non-contrast CT images to exclude the presence of hemorrhage, time-resolved cone beam CT angiography to evaluate the site of occlusion and collaterals, and CT perfusion parametric images to assess the extent of ischemic core and penumbra, thereby fulfilling the imaging requirements for one-stop-shop imaging in an angiography suite. Adding further value is the ability to obtain these images with such low levels of radiation exposure that multiple assessments during an intervention become feasible. Therefore, in this proposal, the theme is to use this innovation in technology to take a quantum leap forward in clinical practice. To fully optimize and validate the proposed imaging workflow for acute ischemic stroke diagnosis and treatment, three aims are planned using both an animal model and human subject studies. The purpose of Aim #1 is to develop and optimize the SMART-RECON technique to enable One-Stop-Shop imaging; Aim #2 is to validate One-Stop-Shop workflow in animal studies; and Aim #3 is to validate One-Stop-Shop imaging in a two-phase human subject studies. Upon the completion of the proposed aims and the associated quantifiable milestones, a new neurovascular imaging platform should have been developed and tested in clinical environment. It will provide image guidance for diagnosis, patient selection, treatment planning, treatment delivery, and treatment efficacy assessment in patients presenting with an AIS. It is impossible to overstate the degree to which Time is Brain in patients with an AIS. Thus, a workflow which can save time compared to current techniques enabled by the proposed revolutionary imaging technology should allow for a quantum leap in diagnosis and treatment for patients suffering from an acute ischemic stroke.